Search Results (102)

Recently, the usage of mobile phone-based games has increased due to the growing accessibility and convenience they provide. Using a descriptive-quantitative design, a disaster-based mobile application was developed in this study to enhance disaster literacy among the private senior high schools in science, technology, engineering, and mathematics (STEM) education in Davao City, the Philippines. The developed application was provided together with survey questionnaires to 364 students randomly selected from different schools in Davao City usingF a simple random sampling method. The technology acceptance (TAM) model was used to explain how users accepted the new technology. The mobile application was designed with features in four disaster scenarios—fire, flood, volcano, and earthquake. The results revealed a high acceptance, with an average score of the perceived usefulness (PE) of 4.52, perceived ease of use (PEOU) of 4.44, and a behavioral intention (BI) of 4.12. The students accepted the application to enhance disaster risk reduction and management. Aligned with SDG 4 and SDG 11, the application can be used to equip users with the knowledge to respond to disasters and ensure community resilience. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

The increasing number of natural and man-made disasters registered at the global level is causing a significant amount of damage. This represents one of the main sustainability challenges at the global level. The collapse of the Twin Towers, Hurricane Katrina, and the nuclear accident at the Fukushima power plant are some of the most representative disaster events that occurred at the beginning of the third millennium. These relevant disasters need an enhanced level of preparedness to reduce the gaps between the plan and its implementation. Among these actions, training and exercises play a relevant role because they increase the capability of planners, managers, and the people involved. By focusing on the exposure risk component, the general objective of the research is to obtain quantitative evaluations of the exercise’s contribution to risk reduction through evacuation. The paper aims to analyze serious games using a set of methods and models that simulate an urban risk reduction plan. In particular, the paper proposes a transparent framework that merges transport risk analysis (TRA) and transport system models (TSMs), developing serious game activities with the support of emerging information and communication technologies (e-ICT). Transparency is possible through the explicitation of reproducible analytical formulations and linked parameters. The core framework of serious games is constituted by a set of models that reproduce the effects of players’ choices, including planned actions of decisionmakers and travel users’ choices. The framework constitutes the prototype of a digital platform in a “non-stressful” context aimed at providing more insights about the effects of planned actions. The proposed framework is characterized by transparency, a feature that allows other analysts and planners to reproduce each risk scenario, by applying TRA and relative effects simulations in territorial contexts by means of TSMs and parameters updated by e-ICT. A basic experimentation is performed by using a game, presenting the main results of a prototype test based on a reproducible exercise. The prototype experiment demonstrates the efficacy of increasing preparedness levels and reducing exposure by designing and implementing a serious game. The paper’s methodology and results are useful for policymakers, emergency managers, and the community for increasing the preparedness level. Full article

Mining activities in Pakistan’s mineral-rich provinces threaten freshwater security through groundwater depletion, contamination, and flood-induced pollution. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework integrating governance, social, environmental, and technical (GSET) dimensions to holistically assess mining-induced water hazards across Balochistan, Khyber Pakhtunkhwa, and Punjab. Using GIS-based spatial risk mapping with multi-layer hydrological modeling, we combine computational analysis and participatory validation to identify vulnerability hotspots and prioritize high-risk mines. Community workshops involving women water collectors, indigenous leaders, and local experts enhanced map accuracy by translating indigenous knowledge into spatially referenced mitigation plans and integrating gender-sensitive metrics to address gendered water access disparities. Key findings reveal severe groundwater depletion, acid mine drainage, and gendered burdens near Saindak and Cherat mines. Multi-sectoral engagements secured corporate commitments for water stewardship and policy advances in inclusive governance. The framework employs four priority-ranked risk categories (Governance-Economic 15%, Social-Community 30%, Environmental 40%, Technical-Geological 15%) derived via local stakeholder collaboration, enabling context-specific interventions. Despite data limitations, the GIS-driven methodology provides a scalable model for regions facing socio-environmental vulnerabilities. The results demonstrate how community participation directly shaped village-level water management alongside GSET analysis to craft equitable risk reduction strategies. Spatially explicit risk maps guided infrastructure upgrades and zoning regulations, advancing SDG 6 and 13 progress in Pakistan. This work underscores the value of inclusive, weighted frameworks for sustainable mining–water nexus management in Pakistan and analogous contexts. Full article

With increasing wildfire impacts on communities in high-latitude areas, a call for community involvement in wildfire risk reduction has been widely promoted. Correspondingly, a ‘community-based’ approach has been advocated in research understanding wildfire, with various interpretations of ‘community’ evident in this work. This paper conducted a scoping review to identify and characterise how ‘community’ has been conceptualised and operationalised in research on wildfire risk reduction in high-latitude areas (defined as areas above 50° N). Thirty-one in-scope studies were screened by their interpretations of ‘community’ from the following six dimensions: research background, community role and function, social inclusion and exclusion, participatory approach, power relations, and research innovation and reflexivity. We find that the understanding of ‘community’ has expanded beyond its geographical scale in wildfire research, with increasing recognition and inclusion of diverse demographic attributes. Recent research has increasingly focused on, and worked with, Indigenous Nations, as well as certain community attributes. However, ambiguity over what ‘community’ means exists in wildfire research, with ‘community’ passive participation (13 out of 31) in the research and inadequate critical research reflexivity of the community-based approach (29 of 31). We therefore suggest a critical reflection of the community-based approach in future wildfire research and emphasise community heterogeneity in addressing the impacts of climate change. Full article

The growing frequency and severity of climate-induced disasters—such as floods, heatwaves, droughts, and wildfires—pose significant threats to sustainable development worldwide. Integrating Climate Change Adaptation (CCA) and Disaster Risk Reduction (DRR) has emerged as a strategy imperative for enhancing societal resilience and protecting developmental gains. This review synthesizes the current knowledge and practice at the intersection of CCA and DRR, drawing on international frameworks, national policies, and local implementation strategies. We assess the role of the Sendai Framework for Disaster Risk Reduction (2015–2030), the Paris Agreement, and the 2030 Agenda for Sustainable Development in promoting policy coherence and multi-level governance. Particular attention is given to the effectiveness of Nature-Based Solutions (NBS), Ecosystem-Based Adaptation (EbA), and community-based approaches that address both climate vulnerabilities and disaster risks while delivering co-benefits for ecosystems and livelihoods. Case studies from regions highly exposed to climate-related hazards, including the Global South and Europe, illustrate how integrated approaches are operationalized and what barriers persist, including institutional silos, limited financing, and data gaps. For example, Bangladesh has achieved over a 70% reduction in flood-related mortality, while Kenya’s drought-resilient agriculture has increased food security by 35% in affected regions. The review highlights best practices in risk-informed planning, participatory decision-making, and knowledge co-production, emphasizing the need for inclusive governance and cross-sector collaboration. By critically examining the synergies and trade-offs between adaptation and risk reduction, this paper offers a pathway to more resilient, equitable, and sustainable development. It concludes with recommendations for enhancing integration at the policy and practice levels, supporting both immediate risk management and long-term transformation in a changing climate. Full article

The northern foothills of the Qinling Mountains, a critical ecological barrier and urban–rural transition zone in China, face intensifying rainstorm–flood disasters under climate extremes and rapid urbanization. This study pioneers a remote sensing-driven, dynamically coupled framework by integrating multi-source satellite data, system resilience theory, and spatial modeling to develop a novel “risk identification–resilience assessment–scenario simulation” chain. This framework quantitatively evaluates the nonlinear response mechanisms of town–village systems to flood disasters, emphasizing the synergistic effects of spatial scale, morphology, and functional organization. The proposed framework uniquely integrates three innovative modules: (1) a hybrid risk identification engine combining normalized difference vegetation index (NDVI) temporal anomaly detection and spatiotemporal hotspot analysis; (2) a morpho-functional resilience quantification model featuring a newly developed spatial morphological resilience index (SMRI) that synergizes landscape compactness, land-use diversity, and ecological connectivity through the entropy-weighted analytic hierarchy process (AHP); and (3) a dynamic scenario simulator embedding rainfall projections into a coupled hydrodynamic model. Key advancements over existing methods include the multi-temporal SMRI and the introduction of a nonlinear threshold response function to quantify “safe-fail” adaptation capacities. Scenario simulations reveal a reduction in flood losses under ecological priority strategies, outperforming conventional engineering-based solutions by resilience gain. The proposed zoning strategy prioritizing ecological restoration, infrastructure hardening, and community-based resilience units provides a scalable framework for disaster-adaptive spatial planning, underpinned by remote sensing-driven dynamic risk mapping. This work advances the application of satellite-aided geospatial analytics in balancing ecological security and socioeconomic resilience across complex terrains. Full article

The transition from open pit to underground mining intensifies water-related hazards such as Acid Mine Drainage (AMD), groundwater contamination, and aquifer depletion, threatening ecological and socio-economic sustainability. This study develops an Inclusive Disaster Risk Reduction (IDRR) framework using a Multi-Dimensional Risk (MDR) approach to holistically assess water hazards in China’s mining regions, integrating environmental, social, governance, economic, technical, community-based, and technological dimensions. A Multi-Criteria Decision-Making (MCDM) model combining the Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) evaluates risks, enhanced by a Z-number Fuzzy Delphi AHP (ZFDAHP) spatiotemporal model to dynamically weight hazards across temporal (short-, medium-, long-term) and spatial (local to global) scales. Applied to the Sijiaying Iron Mine, AMD (78% severity) and groundwater depletion (72% severity) emerge as dominant hazards exacerbated by climate change impacts (36.3% dynamic weight). Real-time IoT monitoring systems and AI-driven predictive models demonstrate efficacy in mitigating contamination, while gender-inclusive governance and community-led aquifer protection address socio-environmental gaps. The study underscores the misalignment between static regulations and dynamic spatiotemporal risks, advocating for Lifecycle Assessments (LCAs) and transboundary water agreements. Policy recommendations prioritize IoT adoption, carbon–water nexus incentives, and Indigenous knowledge integration to align mining transitions with Sustainable Development Goals (SDGs) 6 (Clean Water), 13 (Climate Action), and 14 (Life Below Water). This research advances a holistic strategy to harmonize mineral extraction with water security, offering scalable solutions for global mining regions facing similar ecological and governance challenges. Full article

On 29 October 2024, Spain suffered the impact of an Isolated Depression at High Levels (DANA) that caused severe human and material damage. As seen in cases of natural disasters of similar magnitudes, the impact on children requires sustained interventions, with educational communities being key settings for providing protection and accompaniment. Although numerous studies highlight the role of schools in preventing and mitigating the socio-emotional impact of natural disasters on children, the literature on concrete educational actions to address the consequences of flood disasters is limited. This study analyses the co-creation process of six actions developed between researchers and teachers from 18 schools in the most affected areas of Valencia. For this purpose, a communicative research methodology was used. The techniques used to co-create actions were six dialogic focus groups, one dialogical scientific gathering and one WhatsApp community with teachers affected by the DANA. The results provide information on the redevelopment of the following six evidence-based actions and their impacts in the first weeks after the DANA: (1) the mapping of educational communities; (2) the planning of dialogic gatherings; (3) the creation of solidarity networks; (4) the creation of optimal learning environments; (5) the preservation of violence-free networks; and (6) the giving of specific support to vulnerable groups. The study offers guidelines for educational practises in flood-related disaster interventions, focusing on enhancing community resilience. Full article

Research on hurricane impacts in Florida’s coastal regions has been extensive, yet there remains a gap in comparing the effects and potential damage of different hurricanes within the same geographical area. Additionally, there is a need for reliable discussions on how variations in storm surges during these events influence evacuation accessibility to hurricane shelters. This is especially significant for rural areas with a vast number of aging populations, whose evacuation may require extra attention due to their special needs (i.e., access and functional needs). Therefore, this study aims to address this gap by conducting a comparative assessment of storm surge impacts on the evacuation accessibility of southwest Florida communities (e.g., Lee and Collier Counties) affected by two significant hurricanes: Irma in 2017 and Ian in 2022. Utilizing the floating catchment area method and examining Replica’s OD Matrix data with Geographical Information Systems (GISs)-based technical tools, this research seeks to provide insights into the effectiveness of evacuation plans and identify areas that need enhancements for special needs sheltering. By highlighting the differential impacts of storm surges on evacuation accessibility between these two hurricanes, this assessment contributes to refining disaster risk reduction strategies and has the potential to inform decision-making processes for mitigating the impacts of future coastal hazards. Full article

Driven by the growing frequency of flood risks, this study focused on farming water resource management (FWRM) as an ecosystem-based solution. Despite its significance, there are limited studies investigating paddy farmers’ community-based adaptations (CBAs) for managing diverse farming water resources at a micro-spatial level, particularly within multidimensional communities. This study aims to bridge this gap and focuses on how community diversity and household characteristics impact farmers’ adaptation to different CBA methods. We conducted a household questionnaire survey in floodplain paddy farming communities in Kawasoti Municipality, Nepal, based on cultural, socioeconomic, and settlement diversity. The questionnaire was subjected to farmers’ CBAs for integrated FWRM and multiple structural and nonstructural adaptation measures for irrigation and rivers. The results showed that farmer participation varied across community groups. To understand the most important associated factors within community diversity and household attributes to adopt different water resources, the most adopted structural measures of water flow management (54%) from irrigation and buffer zone vegetation (54%) from rivers were analyzed. We used the Chi-squared Automatic Interaction Detector model, which suggests that water accessibility associated with community diversity, landholding, and water intake is important to improve farmers’ participation in irrigation management. However, for river management, community diversity, which relates to location in relation to a river and is associated with household income and farmland distance, is an important factor. Full article

With the increasing and intensifying effects of global climate change and the rapid development of higher education, energy and resource consumption at university campuses has been rising drastically. This shift has been worsened by campuses’ expanded role in addressing extreme weather hazards and taking on additional cultural and community functions. This article carries out a comprehensive literature review of the low-carbon measures and resilient behaviors implemented on university campuses based on publications published in two major databases, the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS). Results show that: (1) most existing studies only focus on campus carbon emission reduction from a single perspective, without considering the correlation between carbon emissions in different dimensions on campuses and without analyzing the causes of excessive campus carbon emissions from the perspective of the built environment; (2) current studies have not constructed an assessment system for campus carbon resilience and lack the tools and methods for assessment. After summarizing and analyzing, this study proposes the concept of campus “carbon resilience”, which refers to the ability of campuses to cope with the risks of disasters and uncertainties caused by excessive carbon emissions. The research framework of this study is divided into three parts: connotative characteristics, influencing factors, and optimization strategy. Following this framework, the concept and critical features of campus carbon resilience “carbon minus resilience”, “carbon saving resilience”, “carbon reduction resilience”, and “carbon sequestration resilience” are analyzed and outlined. Next, an integrated impact factor system for campus carbon resilience is proposed. This system incorporates aspects such as land utilization, building operation, landscape creation, and energy regeneration from the perspective of the built environment. Finally, with the core objective of effectively reducing the dynamic range of carbon emissions when dealing with critical disturbances and improving the adaptability and resilience of campuses to cope with excessive carbon emissions, this study proposes an optimization strategy of “setting development goals–establishing an evaluation system–proposing improvement strategies–dynamic feedback and adjustment” to provide ideas and theoretical guidance for responding to university campus carbon risk and planning carbon resilience. Full article

The Himalayan country of Nepal is vulnerable to landslides, earthquakes, and fires. Its inhabitants need to be empowered on how to react in emergencies to prevent fatalities and respond to crises efficiently while promoting longer-term sustainability and resilience. This research project, a collaborative effort involving teachers, students, and researchers, highlights the design and implementation of games for disaster risk reduction tested in remote schools. Three interactive games were developed using an iterative game design process and testing in workshops aiming to ensure the inclusivity and diversity of the project. The games targeted preparedness and response to landslides, earthquakes, and house fires. The outcome has proven that the game-based approach to teaching and learning is crucial in empowering underserved school children often left out in formal and informal disaster management processes. This study has shown that game-based learning of disaster preparedness and response effectively empowers resource-deficient communities and regions of the Global South. Full article

Geodata, geographical information science (GISc), and GeoAI (geo-intelligence workflows) play an increasingly important role in predictive disaster risk reduction and management (DRRM), aiding decision-makers in determining where and when to allocate resources. There have been discussions on the ethical pitfalls of these predictive systems in the context of DRRM because of the documented cases of biases in AI systems in other socio-technical systems. However, none of the discussions expound on how to audit geo-intelligence workflows for biases from data collection, processing, and model development. This paper considers a case study that uses AI to characterize housing stock vulnerability to flooding in Karonga district, Malawi. We use Friedman and Nissenbaum’s definition and categorization of biases that emphasize biases as a negative and undesirable outcome. We limit the scope of the audit to biases that affect the visibility of different housing typologies in the workflow. The results show how AI introduces and amplifies these biases against houses of certain materials. Hence, a group within the population in the area living in these houses would potentially miss out on DRRM interventions. Based on this example, we urge the community of researchers and practitioners to normalize the auditing of geo-intelligence workflows to prevent information disasters from biases. Full article

With the intensification of global warming and sea level rise, extreme weather and climate events occur frequently, increasing the probability and destructive power of marine disasters. The purpose of this paper is to propose the specific application of artificial intelligence (AI) in marine disaster risk reduction. First, this paper uses computer vision to assess the vulnerability of the target and then uses CNN-LSTM to forecast tropical cyclones. Second, this paper proposes a social media communication mechanism based on deep learning and a psychological crisis intervention mechanism based on AIGC. In addition, the rescue response system based on an intelligent unmanned platform is also the focus of this research. Third, this paper also attempts to discuss disaster loss assessment and reconstruction based on machine learning and smart city concepts. After proposing specific application measures, this paper proposes three policy recommendations. The first one is improving legislation to break the technological trap of AI. The second one is promoting scientific and technological innovation to break through key technologies of AI. The third one is strengthening coordination and cooperation to build a disaster reduction system that integrates man and machine. The purpose of this paper is to reduce the risk of marine disasters by applying AI. Furthermore, we hope to provide scientific references for sustainability and human adaptation to climate change. Full article